Actuarial Analyst

Duties and Responsibilities: Pricing Model Development & Data Science Design, build, and validate predictive pricing models using statistical and machine learning methods, tailored to P&C and reinsurance lines. Develop and maintain end-to-end pricing pipelines, from raw data ingestion and feature engineering through model training, validation, deployment, and monitoring. Apply credibility theory, loss development, trend analysis, and exposure rating in combination with data science techniques to produce robust rate indications. Develop pricing tools and actuarial models that support estimation of price adequacy, rate change measurement, and portfolio segmentation across all assigned lines of business. Automate recurring pricing workflows and reporting using Python, R, or SQL to improve efficiency, consistency, and auditability. Maintain version control and documentation of models, code, and assumptions in alignment with company standards and actuarial professionalism guidelines. Rate Indications & Regulatory Filings Perform regular rate indications for all assigned states and programs using standard actuarial methods, including loss ratio, pure premium, and experience rating approaches. Recommend rate actions with a focus on long-term profitability, market competitiveness, and regulatory feasibility. Research peer company filings and develop actuarially supportable rates in emerging or data-sparse segments. Portfolio & Transactional Pricing Perform portfolio-level and individual account/treaty pricing analyses across property, casualty, specialty, and reinsurance lines. Assist senior staff in review and pricing of new program opportunities, facultative submissions, and treaty structures. Identify areas of strong profitability for growth and underperforming segments for re-underwriting, contraction, or exit. Develop segmental and trend analyses to support underwriting decisions and strategic planning. Performance Monitoring & Analytics Monitor pricing performance metrics including rate change, price adequacy, loss ratio emergence, and plan-vs-actual comparisons. Design and maintain dashboards and reporting tools that deliver actionable pricing intelligence to underwriting teams and senior leadership. Conduct experience studies, parameter reviews, and assumption updates on a defined schedule; present findings and recommendations to key committees. Support reserve reviews for assigned segments and respond to ad hoc data calls from internal and external stakeholders. Cross-Functional Collaboration & Stakeholder Engagement Liaise with Underwriting, Claims, Reserving, Exposure Management, and the Managing Actuary to ensure pricing reflects all relevant loss, exposure, and operational information. Provide training and technical guidance to underwriters on pricing methodology, rate change requirements, and model outputs. Clearly and concisely present findings, model results, and recommendations to diverse audiences including senior actuarial management, underwriting teams, compliance officers, MGU/MGA partners, and regulators. Ensure data quality, integrity, and completeness in pricing tools; identify data gaps and champion improvements. Build and maintain constructive working relationships with internal and external partners identified as key to the role. Process Improvement & Governance Identify opportunities to improve pricing processes, methodologies, and data infrastructure; contribute to and lead delivery of such improvements. Maintain pricing model documentation at required frequency, obtaining appropriate managerial sign-offs and adhering to model governance standards. Understand and apply the company's pricing quality assurance process; support underwriting controls related to pricing and relevant regulatory principles. Keep abreast of industry best practices, emerging data science techniques, new actuarial initiatives, and changes in regulatory requirements. Talent Development & Team Contribution Operate as an effective team member by supporting colleagues and contributing to overall team and business objectives. Pursue actuarial examination progress toward FCAS designation and engage in ongoing professional development.

Basic Qualifications: (i.e. education, certifications, etc.)Bachelor's degree in Actuarial Science, Mathematics, Statistics, Data Science, Computer Science, Economics, or a closely related quantitative field required. Master's degree (M.S. or M.A.) in Actuarial Science, Statistics, Data Science, Applied Mathematics, or a related discipline strongly preferred. Active pursuit of the Casualty Actuarial Society (CAS) Fellowship (FCAS) designation required; ACAS or near-ACAS standing preferred. Supplemental credentials such as CPCU, ARe, CERA, or formal data science certifications (e.g., AWS ML Specialty, Google Professional Data Engineer) are a plus. Experience3 or more years of progressive actuarial experience in property and casualty insurance and/or reinsurance pricing required. Demonstrated experience building and deploying predictive models and pricing tools in a commercial or specialty insurance environment. Experience with rate filing preparation, DOI interactions, and regulatory compliance preferred. Familiarity with MGU/MGA, program, treaty, or facultative reinsurance business structures is a plus. Prior experience working in or alongside data engineering or data science teams preferred. Key Certifications (if applicable)FCAS certification